AI Software Engineer

dotLinkers

United States

Remote

USD 66,000 - 79,000

Full time

6 days ago

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Benefits offered by this job

Open PTO policy

Days of Disconnect

Parental leave

Pet-related leave

Fitness reimbursement

Medical, dental, and vision coverage

EAP

Calm App subscription

Contract up to 310000 PLN gross/year

Job summary

dotLinkers is seeking an AI Software Engineer for a remote contract role to build and deliver AI-powered product features from discovery to production and continuous improvement. You will work with Product and Design on LLMs, RAG, tool calls, and agentic workflows, ensuring secure, high-quality experiences for real customers.

You will define success metrics, create evaluation datasets, and design guardrails and fallbacks to handle uncertain AI outputs, while maintaining prompts, retrieval

Qualifications

Shipping AI-powered features used by real customers.
Strong software engineering skills for production apps/services.
Understanding AI quality, failure analysis, and latency/cost trade-offs.
Experience with prompt engineering, context engineering, retrieval design and tool calling.
Product-oriented thinking turning ambiguous problems into measurable features.
Experience designing fallbacks, guardrails, and UX for low-confidence outputs.
Knowledge of data privacy and multi-tenant security for AI agents.
Ability to verify generated code and recommendations from AI tools.
Production mindset: monitoring, debugging, incident response, continuous improvement.
Clear communication to technical and non-technical stakeholders.

Responsibilities

Own AI-powered product features from problem discovery through launch and improvement.
Collaborate with Product and Design to deliver customer value from AI.
Build and integrate AI features using LLMs, RAG, tool calling, and agentic workflows.
Define success criteria including outcomes, task completion, quality, latency and cost.
Create evaluation datasets from real scenarios to validate releases.
Design UX that handles uncertainty with fallbacks and explanations.
Maintain prompts, context strategies, and retrieval pipelines as tested components.
Apply secure AI practices including tenant data isolation and least-privilege access.
Run experiments and A/B tests to measure impact on outcomes.
Monitor production, troubleshoot, and participate in on-call rotations.
Share feedback with AI Platform and contribute reusable patterns.
Use AI development tools while ensuring code quality.

Skills

AI features

LLM applications

RAG systems

Agent workflows

Production engineering

Prompt engineering

Context design

Tool calling

Security & privacy

Tools

AI coding tools

Job description

Position: AI Software Engineer
Employment: contract of employment up to 25 800 PLN gross/month
Working mode: remote

About our client

Our client is a global technology company providing software solutions for the fitness industry. Its products help fitness clubs, gyms, and studios manage their operations, memberships, payments, and customer engagement. The company is expanding its AI capabilities to bring intelligent automation and AI-powered experiences into its products and internal workflows. Its engineering teams are building a shared AI platform that enables developers to deliver AI-powered features faster, more securely, and more reliably.

About the role

We are looking for an AI Software Engineer to build and deliver AI-powered product features from initial discovery through production and continuous improvement. You will work closely with Product and Design to identify real customer needs and turn them into useful, measurable product capabilities. Your work will involve LLM applications, retrieval-augmented generation (RAG), tool calling, and agentic workflows, integrated into existing products using the company’s shared AI platform. You will be responsible for evaluating feature quality, handling AI failures, protecting customer data, and measuring the impact of your solutions on user experience and business outcomes. This is a hands-on product engineering role focused on shipping reliable AI features that customers actually use and trust, rather than model training or research.

Responsibilities

Own AI-powered product features from problem discovery and design through implementation, launch, adoption, and ongoing improvement.
Collaborate with Product and Design to identify where AI can deliver meaningful customer value.
Build and integrate AI features using LLMs, RAG, tool calling, and agentic workflows.
Define success criteria before development, including user outcomes, task completion, quality, latency, and cost.
Create evaluation datasets based on real customer scenarios and use them to validate releases.
Design user experiences that handle uncertainty and incorrect AI outputs through fallbacks, human review, clear explanations, and correction mechanisms.
Develop and maintain prompts, context strategies, and retrieval pipelines as tested, versioned, and observable components.
Apply secure AI practices, including tenant data isolation, least-privilege tool access, PII protection, and safeguards against prompt injection.
Run experiments and A/B tests to measure the impact of AI features on customer and business outcomes.
Monitor production performance, troubleshoot issues, participate in on-call rotations, and implement improvements following incidents.
Work closely with the AI Platform team to share feedback, requirements, and reusable patterns.
Use coding agents and AI development tools effectively while maintaining strong engineering and code quality standards.

Requirements

Practical experience shipping AI-powered product features, such as LLM applications, RAG systems, or agent-based solutions, used by real customers.
Strong software engineering skills and experience developing and maintaining production applications or services.
Understanding of AI quality evaluation, failure analysis, hallucination mitigation, and the trade-offs between quality, latency, and cost.
Experience with prompt engineering, context engineering, retrieval design, and tool or function calling in production environments.
Product-oriented thinking and the ability to turn ambiguous customer problems into well-defined features with measurable outcomes.
Experience designing fallback mechanisms, guardrails, and user experiences that handle incorrect or low-confidence AI outputs.
Understanding of data privacy, multi-tenant security, and safe permission management for AI agents.
Ability to use AI coding tools while independently verifying generated code and recommendations.
A strong production mindset, including monitoring, debugging, incident response, and continuous improvement.
Excellent communication and collaboration skills, with the ability to explain AI behavior and limitations to technical and non-technical stakeholders.
A customer-focused approach, prioritizing real-world adoption and trust over impressive demonstrations.
Willingness to collaborate with other engineering teams and contribute reusable solutions and best practices.

Nice to have

Experience in fitness, wellness, membership-based businesses, or SaaS products.
Experience building conversational interfaces, AI assistants, or agentic workflows integrated into customer-facing products.
Familiarity with A/B testing, experimentation platforms, and product analytics.
Experience with search, recommendations, personalization, or ranking systems.
Frontend or full-stack engineering experience.
Familiarity with LLM observability, tracing, and user feedback collection.
Experience optimizing AI costs through caching, model selection, or prompt efficiency.
Experience integrating with LLM gateways, evaluation frameworks, or internal AI platforms.

What our client offers